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Adversarial Robustness Certification for Bayesian Neural Networks

Adversarial Robustness Certification for Bayesian Neural Networks

23 June 2023
Matthew Wicker
A. Patané
Luca Laurenti
Marta Z. Kwiatkowska
    AAML
ArXivPDFHTML

Papers citing "Adversarial Robustness Certification for Bayesian Neural Networks"

9 / 9 papers shown
Title
Certificates of Differential Privacy and Unlearning for Gradient-Based
  Training
Certificates of Differential Privacy and Unlearning for Gradient-Based Training
Matthew Wicker
Philip Sosnin
Adrianna Janik
Mark N. Müller
Adrian Weller
Calvin Tsay
MU
29
3
0
19 Jun 2024
Probabilistic Reach-Avoid for Bayesian Neural Networks
Probabilistic Reach-Avoid for Bayesian Neural Networks
Matthew Wicker
Luca Laurenti
A. Patané
Nicola Paoletti
Alessandro Abate
Marta Z. Kwiatkowska
24
2
0
03 Oct 2023
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic
  Programming
BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
Steven Adams
A. Patané
Morteza Lahijanian
Luca Laurenti
AAML
98
7
0
19 Jun 2023
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D
  biomedical image classification
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification
Jiancheng Yang
Rui Shi
D. Wei
Zequan Liu
Lin Zhao
B. Ke
Hanspeter Pfister
Bingbing Ni
VLM
183
648
0
27 Oct 2021
Safe Control with Neural Network Dynamic Models
Safe Control with Neural Network Dynamic Models
Tianhao Wei
Changliu Liu
29
35
0
03 Oct 2021
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
Mohammad Emtiyaz Khan
Didrik Nielsen
Voot Tangkaratt
Wu Lin
Y. Gal
Akash Srivastava
ODL
74
266
0
13 Jun 2018
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
231
1,837
0
03 Feb 2017
Safety Verification of Deep Neural Networks
Safety Verification of Deep Neural Networks
Xiaowei Huang
M. Kwiatkowska
Sen Wang
Min Wu
AAML
180
932
0
21 Oct 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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